distilbert-rating-regression-rob-dset
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1938
- Accuracy: 0.5579
- Mse: 0.6630
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Mse |
|---|---|---|---|---|---|
| No log | 1.0 | 425 | 1.0287 | 0.5356 | 0.7750 |
| 1.1536 | 2.0 | 850 | 1.0397 | 0.5328 | 0.6829 |
| 0.8897 | 3.0 | 1275 | 1.0515 | 0.5565 | 0.6503 |
| 0.6831 | 4.0 | 1700 | 1.1938 | 0.5579 | 0.6630 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1